基于层次聚类方法的东爪哇县域/城市人类发展指数数据分组分析

Roudlotul Jannah Alfirdausy, Nurissaidah Ulinnuha, Moh. Hafiyusholeh
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引用次数: 0

摘要

人类发展的评价通常是使用人类发展指数(HDI)来完成的,它根据生活质量的各个基本方面来衡量发展水平。在东爪哇,人类发展指数被归类为高。然而。东爪哇各县/城市的人类发展指数分布仍然不均衡。因此,有必要根据地区/城市的人类发展指数和对人类发展指数有贡献的每个指标的实现情况对其进行分类。聚类是一种数据分析技术,用于将相似的数据分组在一起。分层凝聚聚类是用于此目的的方法之一。本研究旨在为政府了解东爪哇省各区/市的HDI分布特征提供参考。对东爪哇2021年HDI数据的分析表明,使用Average Linkage获得的方法和聚类最好,其相关系数值为0.8105891,得到两个聚类。剪影系数值最高的聚类包括34个区/市,为低聚类,高聚类包括4个市/县。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Regency/City Human Development Index Data in East Java Through Grouping Using Hierarchical Agglomerative Clustering Method
The evaluation of human development is typically done using the Human Development Index (HDI), which measures the level of development in terms of various essential aspects of quality of life. In the case of East Java, the HDI is categorized as high. However. the distribution of HDI among the Regencies/Cities in East Java is still uneven. Therefore, it becomes necessary to cluster the districts/cities based on their HDI and the achievement of each indicator contributing to the HDI. Clustering is a data analysis technique used to group similar data together. Hierarchical agglomerative clustering is one of the methods used for this purpose. The aim of this study is to provide a reference for the government to understand the distribution of characteristic groupings among the districts/cities based on their HDI profiles in East Java. The analysis of East Java's HDI data for 2021 revealed that the best method and cluster was obtained using Average Linkage, with a Cophenetic coefficient value of 0.8105891, resulting in two clusters. The cluster with the highest Silhouette coefficient value of 0.6196077 comprised 34 districts/cities, classified as the low cluster, while the high cluster consisted of four cities/regencies.
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